Detection and characterization of isolated and overlapping spots
Computer Vision and Image Understanding
A Markov Random Field model of microarray gridding
Proceedings of the 2003 ACM symposium on Applied computing
Robust DNA microarray image analysis
Machine Vision and Applications
A Markov Random Field Approach to Microarray Image Gridding
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
A Hill-Climbing Approach for Automatic Gridding of cDNA Microarray Images
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Recognition of perspectively distorted planar grids
Pattern Recognition Letters
Information Sciences: an International Journal
A Deformable Grid-Matching Approach for Microarray Images
IEEE Transactions on Image Processing
Sub-grid and spot detection in DNA microarray images using optimal multi-level thresholding
PRIB'10 Proceedings of the 5th IAPR international conference on Pattern recognition in bioinformatics
Biological assessment of grid and spot detection in cDNA microarray images
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Applications of multilevel thresholding algorithms to transcriptomics data
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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Analysis of DNA microarray images is a crucial step in gene expression analysis, as it influences the whole process for obtaining biological conclusions. When processing the underlying images, accurately separating the subgrids is of supreme importance for subsequent steps. A method for separating the sub-grids is proposed, which aims to first, detect rotations in the images independently for the x and y axes, corrected by an affine transformation, and second, separate the corresponding sub-grids in the corrected image. Extensive experiments performed in various real-life microarray images from different sources show that the proposed method effectively detects and corrects the underlying rotations and accurately finds the sub-grid separations.